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Record W3203557690 · doi:10.1111/obr.13368

Caesarean section and obesity in young adult offspring: Update of a systematic review with meta‐analysis

2021· review· en· W3203557690 on OpenAlexaff
Berenike Quecke, Yannick Graf, Adina Mihaela Epure, Valérie Santschi, Arnaud Chioléro, Cristian Carmeli, Stéphane Cullati

Bibliographic record

VenueObesity Reviews · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsMcGill University
FundersHaute école Spécialisée de Suisse Occidentale
KeywordsMeta-analysisCaesarean sectionOffspringMedicineObesitySection (typography)Systematic reviewMEDLINEObstetricsPregnancyInternal medicineBiologyComputer science

Abstract

fetched live from OpenAlex

Summary As compared with vaginal delivery (VD), caesarean section (CS) birth could be associated with increased risk of obesity in young adult offspring. We aimed to evaluate this association by updating data from a systematic review with meta‐analysis of observational studies. From 3774 records identified in PubMed and Embase, we retained six studies and added five studies from the last systematic review, for a total of 11 studies. Crude estimates of the association were retrieved from nine cohort studies ( n = 143,869), and maximally adjusted estimates were retrieved from eight cohort studies. Young adults born by CS had higher risk of obesity (body mass index [BMI] ≥ 30 kg/m 2 ) than young adults born by VD, corresponding to a crude pooled risk ratio (RR) of 1.30 [95% confidence interval (CI) 1.13 to 1.50] and a maximally adjusted pooled RR of 1.22 [95% CI 1.02 to 1.46]. In a sensitivity analysis pooling, five studies that included maternal prepregnancy BMI, a major potential confounding factor, in the set of controlled covariates, the RR was 1.08 [95% CI 0.92 to 1.27]. We concluded that the association between CS and obesity in young adulthood was mostly explained by confounding from maternal prepregnancy BMI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.341
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2021
Admission routes1
Has abstractyes

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